System and method for reading and writing to big data storage formats

ABSTRACT

A system may receive a request for access to a first variable. The request may include a requested action and a variable identifier for the first variable. The request may also have a syntax that is incompatible with first data storage format. The system may parse the request to capture the variable identifier from the request. The system may also look up a location of the first variable in a catalog using the variable identifier. The location of the first variable may include the first data storage format. The system may generate a query to access the first variable. The syntax of the query may be compatible with the first data storage format. The system may then submit the query to the first data storage format. The query may be configured to complete the requested action.

FIELD

The present disclosure relates to systems for reading and writing datato varying big data storage formats.

BACKGROUND

Large data sets may exist in various sizes and organizationalstructures. With big data comprising data sets as large as ever, thevolume of data collected incident to the increased popularity of onlineand electronic transactions continues to grow. For example, billions ofrecords (also referred to as rows) and hundreds of thousands of columnsworth of data may populate a single table. The large volume of data maybe collected in a raw, unstructured, and undescriptive format in someinstances. However, traditional relational databases may not be capableof sufficiently handling the size of the tables that big data creates.

As a result, the massive amounts of data in big data sets may be storedin numerous different data storage formats in various locations toservice diverse application parameters and use case parameters. Eachdifferent data storage format typically has a different interfaceapproach as well. For users, the difficulty of learning the variousinterface protocols, each having varying query syntaxes and adaptingprograms to interact with multiple storage formats, creates difficultiesfor users of big data formats. In big data, different applications mayoperate best on different storage formats. For example, an applicationneeding a near-instantaneous response time for a user experience maydemand a platform designed to return fast query results. In someinstances, a preferred query syntax or language for use in a particularapplication may be incompatible with well-suited storage formats for theapplication.

SUMMARY

A system, method, and computer readable medium (collectively, the“system”) is disclosed for providing controlled read and write access tovarious big data storage formats. The system may receive a request foraccess to a first variable. The request may include a requested actionand a variable identifier for the first variable. The request may alsohave a syntax that is incompatible with first data storage format. Thesystem may parse the request to capture the variable identifier from therequest. The system may also look up a location of the first variable ina catalog using the variable identifier. The location of the firstvariable may include the first data storage format. The system maygenerate a query to access the first variable. The syntax of the querymay be compatible with the first data storage format. The system maythen submit the query to access the first data storage format. The querymay be configured to complete the requested action.

In various embodiments, the system may check an access permission forthe first variable and deny the request at least partially in responseto the access permission. The access permission may indicate that therequest does not have permission to access the first variable. Thesystem may format a result of the requested action into a requestedresult format with data from the first data storage format. The systemmay further generate a log entry corresponding to the request andcomprising a user identifier and/or an application identifier. Thesystem may receive the request for access to a second variable stored ina second data storage format with the second data storage formatdifferent from the first data storage format, and the system may thenreturn a result of the requested action. The result may include thefirst variable from the first data storage format and the secondvariable from the second data storage format. The system may also writedata to the first variable in the first data storage format in responseto the request.

The forgoing features and elements may be combined in variouscombinations without exclusivity, unless expressly indicated hereinotherwise. These features and elements as well as the operation of thedisclosed embodiments will become more apparent in light of thefollowing description and accompanying drawings.

BRIEF DESCRIPTION

The subject matter of the present disclosure is particularly pointed outand distinctly claimed in the concluding portion of the specification. Amore complete understanding of the present disclosure, however, may beobtained by referring to the detailed description and claims whenconsidered in connection with the drawing figures, wherein like numeralsdenote like elements.

FIG. 1 illustrates an exemplary system for storing, reading, and writingbig data sets, in accordance with various embodiments;

FIG. 2 illustrates an exemplary big data management system supporting aunified, virtualized interface for multiple data storage formats, inaccordance with various embodiments;

FIG. 3 illustrates an exemplary process for providing a virtualizeddatabase structure that appears as a single data storage format to aclient but interacts with various multiple data storage formats to readand write data, in accordance with various embodiments;

FIG. 4 illustrates an exemplary architecture for a big data accessinterface system, in accordance with various embodiments; and

FIG. 5 illustrates an exemplary process for accessing data in responseto queries from applications and use cases with the data located invarious data storage formats having differing syntax, in accordance withvarious embodiments.

DETAILED DESCRIPTION

The detailed description of various embodiments herein makes referenceto the accompanying drawings and pictures, which show variousembodiments by way of illustration. While these various embodiments aredescribed in sufficient detail to enable those skilled in the art topractice the disclosure, it should be understood that other embodimentsmay be realized and that logical and mechanical changes may be madewithout departing from the spirit and scope of the disclosure. Thus, thedetailed description herein is presented for purposes of illustrationonly and not of limitation. For example, the steps recited in any of themethod or process descriptions may be executed in any order and are notlimited to the order presented. Moreover, any of the functions or stepsmay be outsourced to or performed by one or more third parties.Furthermore, any reference to singular includes plural embodiments, andany reference to more than one component may include a singularembodiment.

As used herein, “big data” may refer to partially or fully structured,semi-structured, or unstructured data sets including hundreds ofthousands of columns and records. A big data set may be compiled, forexample, from a history of purchase transactions over time, from webregistrations, from social media, from records of charge (ROC), fromsummaries of charges (SOC), from internal data, and/or from othersuitable sources. Big data sets may be compiled with or withoutdescriptive metadata such as column types, counts, percentiles, and/orother interpretive-aid data points. The big data sets may be stored invarious big-data storage formats containing millions of records (i.e.,rows) and numerous variables (i.e., columns) for each record.

The present disclosure provides a system, method, and computer programproduct for querying various data storage formats with a preferredlanguage. Differing data storage formats may be compatible with variousquery languages, syntaxes, and/or interfaces. For example, SQL-typequeries written in the hive query language (HQL) may be used to accessdata stored in Hive® data storage format. However, the same SQL-typequeries may not be used to access data stored in an HBase storagesystem, which relies on a noSQL interface to retrieve stored data. Aunified virtualized database layer may provide an interface to interactwith the Hive® and HBase data storage formats, as well as any other bigdata storage formats, using a uniform query language to retrieve, write,read, and otherwise work with stored data. A big data reader/writer maythen parse and translate queries written in various languages into theunified virtualized database interface language or directly into thevarious languages of the various data storage formats. Users may writequeries in their preferred query language or interface to access dataand/or data storage formats that may typically be incompatible withtheir preferred query language or format.

With reference to FIG. 1, a distributed file system (DFS) 100 is shown,in accordance with various embodiments. DFS 100 comprises a distributedcomputing cluster 102 configured for parallel processing and storage.Distributed computing cluster 102 may comprise a plurality of nodes 104in electronic communication with each of the other nodes, as well as acontrol node 106. Processing tasks may be split among the nodes ofdistributed computing cluster 102 to improve throughput and enhancestorage capacity. Distributed computing cluster 102 may be, for example,a Hadoop® cluster configured to process and store big data sets withsome of nodes 104 comprising a distributed storage system and some ofnodes 104 comprising a distributed processing system. In that regard,distributed computing cluster 102 may be configured to support a Hadoop®distributed file system (HDFS) as specified by the Apache SoftwareFoundation at http://hadoop.apache.org/docs/.

In various embodiments, nodes 104, control node 106, and client 110 maycomprise any devices capable of receiving and/or processing anelectronic message via network 112 and/or network 114. For example,nodes 104 may take the form of a computer or processor, or a set ofcomputers/processors, such as a system of rack-mounted servers. However,other types of computing units or systems may be used, includinglaptops, notebooks, hand held computers, personal digital assistants,cellular phones, smart phones (e.g., iPhone®, BlackBerry®, Android®,etc.) tablets, wearables (e.g., smart watches and smart glasses), or anyother device capable of receiving data over the network.

In various embodiments, client 110 may submit requests to control node106. Control node 106 may distribute the tasks among nodes 104 forprocessing to complete the job intelligently. Control node 106 may thuslimit network traffic and enhance the speed at which incoming data isprocessed. In that regard, client 110 may be a separate machine fromdistributed computing cluster 102 in electronic communication withdistributed computing cluster 102 via network 112. A network may be anysuitable electronic link capable of carrying communication between twoor more computing devices. For example, network 112 may be local areanetwork using TCP/IP communication or wide area network usingcommunication over the Internet. Nodes 104 and control node 106 maysimilarly be in communication with one another over network 114. Network114 may be an internal network isolated from the Internet and client110, or, network 114 may comprise an external connection to enabledirect electronic communication with client 110 and the internet.

A network may be unsecure. Thus, communication over the network mayutilize data encryption. Encryption may be performed by way of any ofthe techniques now available in the art or which may becomeavailable—e.g., Twofish, RSA, El Gamal, Schorr signature, DSA, PGP, PKI,GPG (GnuPG), and symmetric and asymmetric cryptography systems.

In various embodiments, DFS 100 may process hundreds of thousands ofrecords from a single data source. DFS 100 may also ingest data fromhundreds of data sources. Nodes 104 may process the data in parallel toexpedite the processing. Furthermore, the transformation and intake ofdata as disclosed below may be carried out in memory on nodes 104. Forexample, in response to receiving a source data file of 100,000 records,a system with 100 nodes 104 may distribute the task of processing 1,000records to each node 104. Each node 104 may then process the stream of1,000 records while maintaining the resultant data in memory until thebatch is complete for batch processing jobs. The results may be written,augmented, logged, and written to disk for subsequent retrieval. Theresults may be written to disks using various big data storage formats.

With reference to FIG. 2, an exemplary architecture of a big datamanagement system (BDMS) 200 is shown, in accordance with variousembodiments. BDMS 200 may by similar to or identical to DFS 100 of FIG.1, for example. DFS 202 may serve as the physical storage medium for thevarious data storage formats 201 of DFS 202. A non-relational database204 may be maintained on DFS 202. For example, non-relational database204 may comprise an HBase™ storage format that provides random, realtime read and/or write access to data, as described and made availableby the Apache Software Foundation at http://hbase.apache.org/.

In various embodiments, a search platform 206 may be maintained on DFS202. Search platform 206 may provide distributed indexing and loadbalancing to support fast and reliable search results. For example,search platform 206 may comprise a Solr® search platform as describedand made available by the Apache Software Foundation athttp://lucene.apache.org/solr/.

In various embodiments, a data warehouse 214 such as Hive® may bemaintained on DFS 202. The data warehouse 214 may support datasummarization, query, and analysis of warehoused data. For example, datawarehouse 214 may be a Hive® data warehouse built on Hadoop®infrastructure. A data analysis framework 210 may also be built on DFS202 to provide data analysis tools on the distributed system. Dataanalysis framework 210 may include an analysis runtime environment andan interface syntax similar to those offered in the Pig platform asdescribed and made available by the Apache Software Foundation athttps://pig.apache.org/.

In various embodiments, a cluster computing engine 212 for high-speed,large-scale data processing may also be built on DFS 202. For example,cluster computing engine 212 may comprise an Apache Spark™ computingframework running on DFS 202. DFS 202 may further support a MapReducelayer 216 for processing big data sets in a parallel, distributed mannerto produce records for data storage formats 201. For example, MapReducelayer 216 may be a Hadoop® MapReduce framework distributed with theHadoop® HDFS as specified by the Apache Software Foundation athttp://hadoop.apache.org/docs/. The cluster computing engine 212 andMapReduce layer 216 may ingest data for processing, transformation, andstorage in data storage formats 201 using the distributed processing andstorage capabilities of DFS 202.

In various embodiments, DFS 202 may also support a table and storagemanagement layer 208 such as, for example, an HCatalog installation.Table and storage management layer 208 may provide an interface forreading and writing data for multiple related storage formats.Continuing the above example, an HCatalog installation may provide aninterface for one or more of the interrelated technologies describedabove such as, for example, Hive®, Pig, Spark®, and Hadoop® MapReduce.

In various embodiments, DFS 202 may also include various other datastorage formats 218. Other data storage formats 218 may have variousinterface languages with varying syntax to read and/or write data. Infact, each of the above disclosed storage formats may vary in querysyntax and interface techniques. Virtualized database structure 220 mayprovide a uniform, integrated user experience by offering users a singleinterface point for the various different data storage formats 201maintained on DFS 202. Virtualized database structure 220 may be asoftware and/or hardware layer that makes the underlying data storageformats 201 transparent to client 222 by providing variables on request.Client 222 may request and access data by requesting variables fromvirtualized database structure 220. Virtualized database structure 220may then access the variables using the various interfaces of thevarious data storage formats 201 and return the variables to client 222.

In various embodiments, the data stored using various above discloseddata storage formats 201 may be stored across data storage formats 201and accessed at a single point through virtualized database structure220. The variables accessible through virtualized database structure 220may be similar to a column in a table of a traditional RDBMS. That is,the variables identify data fields available in the various data storageformats 201.

In various embodiments, variables may be stored in a single one of thedata storage formats 201 or replicated across numerous data storageformats 201 to support different access characteristics. Virtualizeddatabase structure 220 may comprise a catalog of the various variablesavailable in the various data storage formats 201. The catalogedvariables enable BDMS 200 to identify and locate variables stored acrossdifferent data storage formats 201 on DFS 202. Variables may be storedin at least one storage format on DFS 202 and may be replicated tomultiple storage formats on DFS 202. The catalog of virtualized databasestructure 220 may thus track the location of variables available inmultiple storage formats.

The variables may be cataloged as they are ingested and stored usingdata storage formats 201. The catalog may track the location ofvariables by identifying the storage format, the table, and/or thevariable name for each variable available through virtualized databasestructure 220. The catalog may also include metadata describing what thevariables are and where the variables came from such as data type,original source variables, timestamp, access restrictions, sensitivityof the data, and/or other descriptive metadata. For example, internaldata and/or personally identifying information (PII) may be flagged assensitive data subject to access restrictions by metadata correspondingto the variables containing the internal data and/or PII. Metadata maybe copied from the storage formats 201 or generated separately forvirtualized database structure 220.

In various embodiments, virtualized database structure 220 may provide asingle, unified, and virtualized data storage format that cataloguesaccessible variables and provides a single access point for recordsstored on data storage formats 201. Client 222 (which may operate usingsimilar hardware and software to client 110 of FIG. 1) may access datastored in various data storage formats 201 via the virtualized databasestructure 220. In that regard, virtualized database structure 220 may bea single access point for data stored across the various data storageformats 201 on DFS 202.

In various embodiments, virtualized database structure 220 may store andmaintain the catalog of variables including locations and descriptivemetadata, but virtualized database structure 220 may not store theactual data contained in each variable. The data that fills thevariables may be stored on DFS 202 using data storage formats 201.Virtualized database structure 220 may enable read and write access tothe data stored in data storage formats 201 without a client systemhaving knowledge of the underlying data storage formats 201.

With reference to FIG. 3, a process 300 for maintaining a virtualizeddatabase structure using BDMS 200 is shown, in accordance with variousembodiments. BDMS 200 may store a plurality of first records in a firstdata storage format (Block 302). The first records (e.g., rows in atable) may include one or more variables (e.g., columns in a table) witheach variable identifying a data field of the records. The first datastorage format may include one of data storage formats 201 describedabove with reference to FIG. 2.

In various embodiments, BDMS 200 may then store a plurality of secondrecords in a second data storage format (Block 304). The second datastorage format may also comprise one of data storage formats 201described above with reference to FIG. 2. The second data storage formatmay be different than the first data storage format. Thus, the seconddata storage format may use a different interface than the first datastorage format for reading or writing data.

In various embodiments, BDMS 200 may generate a catalog including alocation of the first variable and a location of the second variable(Block 306). The location of the first variable may identify the firstdata storage format as the location of the first variable. Similarly,the location of the second variable may identify the second data storageformat as the location of the second variable. Thus, the first variableand the second variable may be generated and/or stored using differentdata storage formats 201. In that regard, a different interface may beused to read and/or write data of the first variable than is used toread and/or write data of the second variable. The catalog may also begenerated to include metadata describing the details of the variablessuch as, for example, data type, access permission, original sourcevariable, timestamp, description, age, version number, and/ortransformation history.

In various embodiments, BDMS 200 may receive a request to access thefirst variable and/or the second variable (Block 308). The request maynot identify the first data storage format or the second data storageformat. Instead, the request may identify the variable for which accessis requested. BDMS 200 may locate the variable for which access isrequested by consulting the catalog maintained by virtualized databasestructure 220. In that regard, BDMS 200 may provide a unified point ofaccess for the first data storage format and second data storage formatdespite the different data structures of the various data storageformats 201.

In various embodiments, BDMS 200 may access the first variable from thefirst location or the second variable from the second location (Block310). With brief reference to FIG. 2, the request for a variable maycome from a client 222 and may be received by virtualized databasestructure 220 of BDMS 200. Virtualized database structure 220 may thenlook up the requested variable in the catalog to identify the locationof the variable. The location of the variable may include the datastorage format(s) that maintain the variable and an identifier for thevariable within the data storage format (e.g., a table and column numbercorresponding to the variable). The requested variable and correspondingdata may be returned to client 222 that made the request. Virtualizeddatabase structure 220 may thus appear as a single data storage formatto client 222.

With reference to FIG. 4, an access interface system 400 is shown forreading and/or writing data stored in big data storage formats, inaccordance with various embodiments. Raw data 402 is ingested and/orstored in big data storage 404. Big data storage 404 may be a singleorganized database environment such as virtualized database structure220 of FIG. 2. Big data storage 404 may thus comprise multiple datastorage formats, having both compatible and incompatible interfaceprotocols and query syntaxes, and organized into a single logical datastructure as viewed from the application side. For example, a Hive® datastorage format may be a delimited flat file stored to disk across adistributed file system. The Hive® data storage format may also supportSQL-type queries for data access. However, the same SQL-type query thatwould successfully retrieve data in Hive® would throw an error in Hbase,as Hbase is not compatible with the SQL-type queries of Hive®.

In various embodiments, an access interface 406 may communicate with bigdata storage 404 to read and write data for use cases and applications408. In that regard, access interface 406 may comprise a softwareinterface that supports the access demands of use cases and applications408. Access interface 406 may run partially or fully on a file systemsuch as DFS 202 to access data via virtualized database structure 220.Access interface 406 may also run partially or fully on a clientcomputer such as client 222. Access interface system may limit directread and write access directly to big data storage 404 by use cases andapplications 408. Instead, use cases and applications 408 may submitrequests for read and write access to data using access interface 406.

In various embodiments, use cases and applications 408 may includeapplications developed using big data storage formats for data demandssuch as external facing applications and internal applications. Usecases and applications 408 may also comprise use cases relying on apreferred big data storage format, such as a Hive® data set, an ApachePig data set, and/or a JSON-like java data set of tuples.

In various embodiments, access interface 406 may accept data accessrequests from use cases and applications 408 in one or more interfaceprotocols and/or syntax. The interface protocols and the interfacesyntaxes suitable for data requests from access interface 406 mayinclude known text-based query syntaxes such as, for example, SQL, HQL,Solr search strings, noSQL javascript search functions, and/or PigLatin.Suitable interface protocols may also include graphical queryconstruction tools available for use with big data technologies such as,for example, Hive®, Hbase, Solr®, Elasticsearch®, Lucene™, ApacheSpark™, Pig, and/or Hadoop® MapReduce. Additionally, an interface tooland/or query language written specifically for access interface 406 maybe used to make read and/or write requests using access interface 406.

In various embodiments, access interface 406 may accept and successfullyparse queries and requests that comply with one or more of the abovementioned interface protocols. Access interface 406 may thus becompatible with one or more of the above mentioned interface protocols.In fact, access interface 406 may be compatible with several of theabove mentioned interface protocols to provide increased flexibility. Inthat regard, use cases and applications 408 may access the data usingtheir preferred data storage format or programming language through asingle, centralized access point created by access interface 406.However, use cases and applications 408 may not write directly to theunderlying data storage formats. With use cases and applications 408using access interface 406 as the sole point of access to underlying bigdata storage 404, access interface 406 may exert access control over thetables, files, records, and data storage formats used in big datastorage 404. At the same time, access interface 406 may restrict usecases and applications 408 from creating and maintaining independentdata stores to service the application demands where such data storesare unnecessarily duplicative.

In various embodiments, use cases and applications 408 may submitrequests to access interface 406 using a compatible syntax and/orinterface protocol. Although the request is compatible with accessinterface 406, the request may not be compatible with the data storageformat in which the data is actually stored in big data storage 404.Thus, access interface 406 may parse the query and identify informationit that it will use to access the selected data in big data storage 404.In that regard, access interface 406 may be big data storage formatagnostic and capable of locating requested data and retrieving the datain the requested format. The request may include one or more piece ofrequest data comprising one or more of a variable identifier such as avariable name, a preferred data storage format, a time, and/or arequestor ID such as a username, a user group, or an application ID.

In various embodiments, access interface 406 may use the request data tolook up the variable in a catalog such as the above described catalog ofvirtualized database structure 220. The catalog may comprise accesspermissions and restrictions for the requesting user and/or applicationas well as the location and format of the requested variable. Accesspermissions may include whether a use case or application 408 has readand/or write access to the requested data, and whether the use case orapplication 408 is authorized to view the information contained in thevariable (for example, in the case of personally identifyinginformation). Access permissions may be catalogued at the file, table,variable, and/or data type levels. Access interface may deny access todata that a requestor does not have sufficient permissions to access bylooking up the access permissions for the requesting user and applyingthem prior to returning a result set. Access interface 406 may log therequest along with the request data for later review.

In various embodiments, access interface system 400 may providecontrolled access to the data in a format that a requesting applicationor use case requests. Access interface 406 may retrieve specificvariables from the data that are responsive to a request by use casesand applications 408. The retrieved data may be formatted into a resultthat would be returned by the requested data storage format even whenthe underlying data is stored in a different data storage format thanrequested. A result set may be compiled and returned to the requestinguse case and application 408 as a result set from a requested datastorage format type. Once prepared, the result set may be returned tothe requestor in the requested format or a suitable format if no formatwas specified. A suitable return format may include the result format ofthe data storage format that is compatible with the interface protocolof the original access request.

With reference to FIG. 5, a process 500 for providing access to big datastorage with access interface 406 is shown, in accordance with variousembodiments. Access interface system 400 may receive a request foraccess to a variable (Block 502). The request may include an action(e.g., read or write) and a variable identifier (e.g., a variableposition, a variable name, a variable ID). The request may include aninterface protocol or interface syntax. In various embodiments, theinterface protocol and/or syntax may be incompatible with the datastorage format in which the variable is stored in big data storage 404.

In various embodiments, the access interface system 400 may parse therequest to capture the variable identifier (Block 504). The variableidentifier may be used to retrieve the location of the variable (e.g.,the data storage format in which the variable is stored) from thecatalog. The variable identifier may also be used to look up relatedmetadata stored in the catalog for the variable such as, for example,access permissions and/or whether the variable contains PII.

In various embodiments, access interface system 400 may look up thelocation of the first variable in the catalog using the variableidentifier (Block 506). The location of the variable may include thedata storage format. Access interface system 400 may then generate aquery to access the first variable (Block 508). The query may have asyntax that is compatible with the data storage format. In that regard,the query may be configured to read and/or write to the data storageformat. Access interface system 400 may then submit the query to thedata storage format (Block 510).

The systems and methods herein provide support access to a wide varietyof data storage formats (e.g., Hive®, Solr®, Hbase) having differentsupport processing approaches (e.g., batch, real-time, process). Theaccess interface enables applications and programmers to access data ina big data environment using the preferred interface application and/orprogramming language through a unified, centralized access point. Theaccess interface is data storage format agnostic and can locate andretrieve data in a requested format. In addition, the data access systemdisclosed herein provides centralized data access and management controlas well as holistic logging utilities. The BDMS of the presentdisclosure may thus reduce the number of copies of data made by clientsby managing access to requested variables and returning the samevariables to multiple clients without making superfluous copies. In thatregard, the BDMS may also ensure that clients are using maintained andupdated data.

Systems, methods and computer program products are provided. In thedetailed description herein, references to “various embodiments”, “oneembodiment”, “an embodiment”, “an example embodiment”, etc., indicatethat the embodiment described may include a particular feature,structure, or characteristic, but every embodiment may not necessarilyinclude the particular feature, structure, or characteristic. Moreover,such phrases are not necessarily referring to the same embodiment.Further, when a particular feature, structure, or characteristic isdescribed in connection with an embodiment, it is submitted that it iswithin the knowledge of one skilled in the art to affect such feature,structure, or characteristic in connection with other embodimentswhether or not explicitly described. After reading the description, itwill be apparent to one skilled in the relevant art(s) how to implementthe disclosure in alternative embodiments.

In various embodiments, the methods described herein are implementedusing the various particular machines described herein. The methodsdescribed herein may be implemented using the below particular machines,and those hereinafter developed, in any suitable combination, as wouldbe appreciated immediately by one skilled in the art. Further, as isunambiguous from this disclosure, the methods described herein mayresult in various transformations of certain articles.

For the sake of brevity, conventional data networking, applicationdevelopment and other functional aspects of the systems (and componentsof the individual operating components of the systems) may not bedescribed in detail herein. Furthermore, the connecting lines shown inthe various figures contained herein are intended to represent exemplaryfunctional relationships and/or physical couplings between the variouselements. It should be noted that many alternative or additionalfunctional relationships or physical connections may be present in apractical system.

The various system components discussed herein may include one or moreof the following: a host server or other computing systems including aprocessor for processing digital data; a memory coupled to the processorfor storing digital data; an input digitizer coupled to the processorfor inputting digital data; an application program stored in the memoryand accessible by the processor for directing processing of digital databy the processor; a display device coupled to the processor and memoryfor displaying information derived from digital data processed by theprocessor; and a plurality of databases. Various databases used hereinmay include: client data; merchant data; financial institution data;and/or like data useful in the operation of the system. As those skilledin the art will appreciate, user computer may include an operatingsystem (e.g., WINDOWS® NT®, WINDOWS® 95/98/2000®, WINDOWS® XP®, WINDOWS®Vista®, WINDOWS® 7®, OS2, UNIX®, LINUX®, SOLARIS®, MacOS, etc.) as wellas various conventional support software and drivers typicallyassociated with computers.

The present system or any part(s) or function(s) thereof may beimplemented using hardware, software or a combination thereof and may beimplemented in one or more computer systems or other processing systems.However, the manipulations performed by embodiments were often referredto in terms, such as matching or selecting, which are commonlyassociated with mental operations performed by a human operator. No suchcapability of a human operator is necessary, or desirable in most cases,in any of the operations described herein. Rather, the operations may bemachine operations. Useful machines for performing the variousembodiments include general purpose digital computers or similardevices.

In fact, in various embodiments, the embodiments are directed toward oneor more computer systems capable of carrying out the functionalitydescribed herein. The computer system includes one or more processors,such as processor. The processor is connected to a communicationinfrastructure (e.g., a communications bus, cross over bar, or network).Various software embodiments are described in terms of this exemplarycomputer system. After reading this description, it will become apparentto a person skilled in the relevant art(s) how to implement variousembodiments using other computer systems and/or architectures. Computersystem can include a display interface that forwards graphics, text, andother data from the communication infrastructure (or from a frame buffernot shown) for display on a display unit.

Computer system also includes a main memory, such as for example randomaccess memory (RAM), and may also include a secondary memory. Thesecondary memory may include, for example, a hard disk drive and/or aremovable storage drive, representing a floppy disk drive, a magnetictape drive, an optical disk drive, etc. The removable storage drivereads from and/or writes to a removable storage unit in a well-knownmanner. Removable storage unit represents a floppy disk, magnetic tape,optical disk, etc. which is read by and written to by removable storagedrive. As will be appreciated, the removable storage unit includes acomputer usable storage medium having stored therein computer softwareand/or data.

In various embodiments, secondary memory may include other similardevices for allowing computer programs or other instructions to beloaded into computer system. Such devices may include, for example, aremovable storage unit and an interface. Examples of such may include aprogram cartridge and cartridge interface (such as that found in videogame devices), a removable memory chip (such as an erasable programmableread only memory (EPROM), or programmable read only memory (PROM)) andassociated socket, and other removable storage units and interfaces,which allow software and data to be transferred from the removablestorage unit to computer system.

Computer system may also include a communications interface.Communications interface allows software and data to be transferredbetween computer system and external devices. Examples of communicationsinterface may include a modem, a network interface (such as an Ethernetaccount), a communications port, a Personal Computer Memory AccountInternational Association (PCMCIA) slot and account, etc. Software anddata transferred via communications interface are in the form of signalswhich may be electronic, electromagnetic, optical or other signalscapable of being received by communications interface. These signals areprovided to communications interface via a communications path (e.g.,channel). This channel carries signals and may be implemented usingwire, cable, fiber optics, a telephone line, a cellular link, a radiofrequency (RF) link, wireless and other communications channels.

The terms “computer program medium” and “computer usable medium” and“computer readable medium” are used to generally refer to media such asremovable storage drive and a hard disk installed in hard disk drive.These computer program products provide software to computer system.

Computer programs (also referred to as computer control logic) arestored in main memory and/or secondary memory. Computer programs mayalso be received via communications interface. Such computer programs,when executed, enable the computer system to perform the features asdiscussed herein. In particular, the computer programs, when executed,enable the processor to perform the features of various embodiments.Accordingly, such computer programs represent controllers of thecomputer system.

In various embodiments, software may be stored in a computer programproduct and loaded into computer system using removable storage drive,hard disk drive or communications interface. The control logic(software), when executed by the processor, causes the processor toperform the functions of various embodiments as described herein. Invarious embodiments, hardware components such as application specificintegrated circuits (ASICs). Implementation of the hardware statemachine so as to perform the functions described herein will be apparentto persons skilled in the relevant art(s).

The various system components may be independently, separately orcollectively suitably coupled to the network via data links whichincludes, for example, a connection to an Internet Service Provider(ISP) over the local loop as is typically used in connection withstandard modem communication, cable modem, Dish Networks®, ISDN, DigitalSubscriber Line (DSL), or various wireless communication methods, see,e.g., GILBERT HELD, UNDERSTANDING DATA COMMUNICATIONS (1996), which ishereby incorporated by reference. It is noted that the network may beimplemented as other types of networks, such as an interactivetelevision (ITV) network. Moreover, the system contemplates the use,sale or distribution of any goods, services or information over anynetwork having similar functionality described herein.

Any databases discussed herein may include relational, nonrelational,hierarchical, graphical, or object-oriented structure and/or any otherdatabase configurations including various big data products availablefrom the Apache Software Foundation as described above. Common databaseproducts that may be used to implement the databases include DB2 by IBM®(Armonk, N.Y.), various database products available from ORACLE®Corporation (Redwood Shores, Calif.), MICROSOFT® Access® or MICROSOFT®SQL Server® by MICROSOFT® Corporation (Redmond, Wash.), MySQL by MySQLAB (Uppsala, Sweden), or any other suitable database product. Moreover,the databases may be organized in any suitable manner, for example, asdata tables or lookup tables. Each record may be a single file, a seriesof files, a linked series of data fields or any other data structure.Association of certain data may be accomplished through any desired dataassociation technique such as those known or practiced in the art. Forexample, the association may be accomplished either manually orautomatically. Automatic association techniques may include, forexample, a database search, a database merge, GREP, AGREP, SQL, using akey field in the tables to speed searches, sequential searches throughall the tables and files, sorting records in the file according to aknown order to simplify lookup, and/or the like. The association stepmay be accomplished by a database merge function, for example, using a“key field” in pre-selected databases or data sectors. Various databasetuning steps are contemplated to optimize database performance. Forexample, frequently used files such as indexes may be placed on separatefile systems to reduce In/Out (“I/O”) bottlenecks.

One skilled in the art will also appreciate that, for security reasons,any databases, systems, devices, servers or other components of thesystem may consist of any combination thereof at a single location or atmultiple locations, wherein each database or system includes any ofvarious suitable security features, such as firewalls, access codes,encryption, decryption, compression, decompression, and/or the like.

Any of the communications, inputs, storage, databases or displaysdiscussed herein may be facilitated through a website having web pages.The term “web page” as it is used herein is not meant to limit the typeof documents and applications that might be used to interact with theuser. For example, a typical website might include, in addition tostandard HTML documents, various forms, JAVA® APPLE®ts, JAVASCRIPT,active server pages (ASP), common gateway interface scripts (CGI),extensible markup language (XML), dynamic HTML, cascading style sheets(CSS), AJAX (Asynchronous JAVASCRIPT And XML), helper applications,plug-ins, and the like. A server may include a web service that receivesa request from a web server, the request including a URL and an IPaddress (123.56.789.234). The web server retrieves the appropriate webpages and sends the data or applications for the web pages to the IPaddress. Web services are applications that are capable of interactingwith other applications over a communications means, such as theinternet. Web services are typically based on standards or protocolssuch as XML, SOAP, AJAX, WSDL and UDDI. Web services methods are wellknown in the art, and are covered in many standard texts. See, e.g.,ALEX NGHIEM, IT WEB SERVICES: A ROADMAP FOR THE ENTERPRISE (2003),hereby incorporated by reference.

Practitioners will also appreciate that there are a number of methodsfor displaying data within a browser-based document. Data may berepresented as standard text or within a fixed list, scrollable list,drop-down list, editable text field, fixed text field, pop-up window,and the like. Likewise, there are a number of methods available formodifying data in a web page such as, for example, free text entry usinga keyboard, selection of menu items, check boxes, option boxes, and thelike.

The system and method may be described herein in terms of functionalblock components, screen shots, optional selections and variousprocessing steps. It should be appreciated that such functional blocksmay be realized by any number of hardware and/or software componentsconfigured to perform the specified functions. For example, the systemmay employ various integrated circuit components, e.g., memory elements,processing elements, logic elements, look-up tables, and the like, whichmay carry out a variety of functions under the control of one or moremicroprocessors or other control devices. Similarly, the softwareelements of the system may be implemented with any programming orscripting language such as C, C++, C#, JAVA®, JAVASCRIPT, VBScript,Macromedia Cold Fusion, COBOL, MICROSOFT® Active Server Pages, assembly,PERL, PHP, awk, Python, Visual Basic, SQL Stored Procedures, PL/SQL, anyUNIX shell script, and extensible markup language (XML) with the variousalgorithms being implemented with any combination of data structures,objects, processes, routines or other programming elements. Further, itshould be noted that the system may employ any number of conventionaltechniques for data transmission, signaling, data processing, networkcontrol, and the like. Still further, the system could be used to detector prevent security issues with a client-side scripting language, suchas JAVASCRIPT, VBScript or the like. For a basic introduction ofcryptography and network security, see any of the following references:(1) “Applied Cryptography: Protocols, Algorithms, And Source Code In C,”by Bruce Schneier, published by John Wiley & Sons (second edition,1995); (2) “JAVA® Cryptography” by Jonathan Knudson, published byO'Reilly & Associates (1998); (3) “Cryptography & Network Security:Principles & Practice” by William Stallings, published by Prentice Hall;all of which are hereby incorporated by reference.

As will be appreciated by one of ordinary skill in the art, the systemmay be embodied as a customization of an existing system, an add-onproduct, a processing apparatus executing upgraded software, astandalone system, a distributed system, a method, a data processingsystem, a device for data processing, and/or a computer program product.Accordingly, any portion of the system or a module may take the form ofa processing apparatus executing code, an internet based embodiment, anentirely hardware embodiment, or an embodiment combining aspects of theinternet, software and hardware. Furthermore, the system may take theform of a computer program product on a computer-readable storage mediumhaving computer-readable program code means embodied in the storagemedium. Any suitable computer-readable storage medium may be utilized,including hard disks, CD-ROM, optical storage devices, magnetic storagedevices, and/or the like.

The system and method is described herein with reference to screenshots, block diagrams and flowchart illustrations of methods, apparatus(e.g., systems), and computer program products according to variousembodiments. It will be understood that each functional block of theblock diagrams and the flowchart illustrations, and combinations offunctional blocks in the block diagrams and flowchart illustrations,respectively, can be implemented by computer program instructions.

These computer program instructions may be loaded onto a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructionsthat execute on the computer or other programmable data processingapparatus create means for implementing the functions specified in theflowchart block or blocks. These computer program instructions may alsobe stored in a computer-readable memory that can direct a computer orother programmable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the function specified in the flowchart block or blocks.The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer-implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Accordingly, functional blocks of the block diagrams and flowchartillustrations support combinations of means for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instruction means for performing the specified functions. Itwill also be understood that each functional block of the block diagramsand flowchart illustrations, and combinations of functional blocks inthe block diagrams and flowchart illustrations, can be implemented byeither special purpose hardware-based computer systems which perform thespecified functions or steps, or suitable combinations of specialpurpose hardware and computer instructions.

The term “non-transitory” is to be understood to remove only propagatingtransitory signals per se from the claim scope and does not relinquishrights to all standard computer-readable media that are not onlypropagating transitory signals per se. Stated another way, the meaningof the term “non-transitory computer-readable medium” and“non-transitory computer-readable storage medium” should be construed toexclude only those types of transitory computer-readable media whichwere found in In Re Nuijten to fall outside the scope of patentablesubject matter under 35 U.S.C. § 101.

Phrases and terms similar to “internal data” may include any data acredit issuer possesses or acquires pertaining to a particular consumer.Internal data may be gathered before, during, or after a relationshipbetween the credit issuer and the transaction account holder (e.g., theconsumer or buyer). Such data may include consumer demographic data.Consumer demographic data includes any data pertaining to a consumer.Consumer demographic data may include consumer name, address, telephonenumber, email address, employer and social security number. Consumertransactional data is any data pertaining to the particular transactionsin which a consumer engages during any given time period. Consumertransactional data may include, for example, transaction amount,transaction time, transaction vendor/merchant, and transactionvendor/merchant location.

Although the disclosure includes a method, it is contemplated that itmay be embodied as computer program instructions on a tangiblecomputer-readable carrier, such as a magnetic or optical memory or amagnetic or optical disk. All structural, chemical, and functionalequivalents to the elements of the above-described exemplary embodimentsthat are known to those of ordinary skill in the art are expresslyincorporated herein by reference and are intended to be encompassed bythe present claims. Moreover, it is not necessary for a device or methodto address each and every problem sought to be solved by the presentdisclosure, for it to be encompassed by the present claims.

Benefits, other advantages, and solutions to problems have beendescribed herein with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any elements that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as critical, required, or essentialfeatures or elements of the disclosure. The scope of the disclosure isaccordingly to be limited by nothing other than the appended claims, inwhich reference to an element in the singular is not intended to mean“one and only one” unless explicitly so stated, but rather “one ormore.” Moreover, where a phrase similar to ‘at least one of A, B, and C’or ‘at least one of A, B, or C’ is used in the claims or specification,it is intended that the phrase be interpreted to mean that A alone maybe present in an embodiment, B alone may be present in an embodiment, Calone may be present in an embodiment, or that any combination of theelements A, B and C may be present in a single embodiment; for example,A and B, A and C, B and C, or A and B and C.

Furthermore, no element, component, or method step in the presentdisclosure is intended to be dedicated to the public regardless ofwhether the element, component, or method step is explicitly recited inthe claims. No claim element herein is to be construed under theprovisions of 35 U.S.C. 112 (f) unless the element is expressly recitedusing the phrase “means for.” As used herein, the terms “comprises”,“comprising”, or any other variation thereof, are intended to cover anon-exclusive inclusion, such that a process, method, article, orapparatus that comprises a list of elements does not include only thoseelements but may include other elements not expressly listed or inherentto such process, method, article, or apparatus.

What is claimed is:
 1. A method comprising: receiving, by a processor, arequest at a single, centralized access point created by an accessinterface for access to a first variable in a single logical datastructure as viewed from an application side, wherein the requestcomprises a requested action and a variable identifier for the firstvariable, wherein the request has a first syntax, wherein a first datastorage format is incompatible with the first syntax; parsing, by theprocessor, the request to capture the variable identifier from therequest; looking up, by the processor, the first variable in a catalogusing the variable identifier, wherein the first variable includes alocation of the first variable and the first data storage format thatmaintains the first variable and the variable identifier within thefirst data storage format; generating, by the processor, a query toaccess the first variable, wherein the query comprises a second syntaxcompatible with the first data storage format; and submitting, by theprocessor, the query to access the first data storage format, whereinthe query is configured to complete the requested action.
 2. The methodof claim 1, further including checking, by the processor, an accesspermission for the first variable in the catalog, wherein the accesspermission includes at least one of read access, write access orauthorization to view information contained in the first variable. 3.The method of claim 1, wherein the variable identifier includes at leastone of a variable name, a preferred data storage format, a time, arequester username, a requester user group, or an application ID.
 4. Themethod of claim 1, further comprising formatting, by the processor, aresult of the requested action into a requested result format, whereinthe result comprises data from the first data storage format.
 5. Themethod of claim 1, further comprising generating, by the processor, alog entry corresponding to the request, wherein the log entry comprisesat least one of a user identifier or an application identifier.
 6. Themethod of claim 1, further comprising: receiving, by the processor, therequest for access to a second variable stored in a second data storageformat, wherein the second data storage format is different from thefirst data storage format; and returning, by the processor, a result ofthe requested action, wherein the result comprises the first variablefrom the first data storage format and the second variable from thesecond data storage format.
 7. The method of claim 1, further comprisingwriting, by the processor, data to the first variable in the first datastorage format in response to the request.
 8. The method of claim 1,wherein the first variable is associated with an access permission,wherein the access permission is cataloged at at least one of a filelevel, table level, variable level or data type level.
 9. The method ofclaim 1, wherein the completing the requested action includes providingthe first variable in the first data storage format, while the firstvariable is stored in a second data storage format.
 10. A computer-basedsystem, comprising: a processor; and a tangible, non-transitory memoryconfigured to communicate with the processor, the tangible,non-transitory memory having instructions stored thereon that, inresponse to execution by the processor, cause an access interface systemto perform operations comprising: receiving, by the processor, a requestat a single, centralized access point created by an access interface foraccess to a first variable in a single logical data structure as viewedfrom an application side, wherein the request comprises a requestedaction and a variable identifier for the first variable, wherein therequest has a first syntax, wherein a first data storage format isincompatible with the first syntax; parsing, by the processor, therequest to capture the variable identifier from the request; looking up,by the processor, the first variable in a catalog using the variableidentifier, wherein the first variable includes a location of the firstvariable and the first data storage format that maintains the firstvariable and the variable identifier within the first data storageformat; generating, by the processor, a query to access the firstvariable, wherein the query comprises a second syntax compatible withthe first data storage format; and submitting, by the processor, thequery to access the first data storage format, wherein the query isconfigured to complete the requested action.
 11. The computer-basedsystem of claim 10, further comprising formatting, by the processor, aresult of the requested action into a requested result format, whereinthe result comprises data from the first data storage format.
 12. Thecomputer-based system of claim 10, further comprising generating, by theprocessor, a log entry corresponding to the request, wherein the logentry comprises at least one of a user identifier or an applicationidentifier.
 13. The computer-based system of claim 10, furthercomprising: receiving, by the processor, the request for access to asecond variable stored in a second data storage format, wherein thesecond data storage format is different from the first data storageformat; and returning, by the processor, a result of the requestedaction, wherein the result comprises the first variable from the firstdata storage format and the second variable from the second data storageformat.
 14. The computer-based system of claim 10, further comprisingwriting, by the processor, data to the first variable in the first datastorage format in response to the request.
 15. An article of manufactureincluding a non-transitory, tangible computer readable storage mediumhaving instructions stored thereon that, in response to execution by aprocessor, cause the processor to perform operations comprising:receiving, by the processor, a request at a single, centralized accesspoint created by an access interface for access to a first variable in asingle logical data structure as viewed from an application side,wherein the request comprises a requested action and a variableidentifier for the first variable, wherein the request has a firstsyntax, wherein a first data storage format is incompatible with thefirst syntax; parsing, by the processor, the request to capture thevariable identifier from the request; looking up, by the processor, thefirst variable in a catalog using the variable identifier, wherein thefirst variable includes a location of the first variable and the firstdata storage format that maintains the first variable and the variableidentifier within the first data storage format; generating, by theprocessor, a query to access the first variable, wherein the querycomprises a second syntax compatible with the first data storage format;and submitting, by the processor, the query to access the first datastorage format, wherein the query is configured to complete therequested action.
 16. The article of claim 15, further including:checking, by the processor, an access permission for the first variable;and denying, by the processor, the request in response to the accesspermission.
 17. The article of claim 16, wherein the access permissionindicates that the request does not have permission to access the firstvariable.
 18. The article of claim 15, further comprising formatting, bythe processor, a result of the requested action into a requested resultformat, wherein the result comprises data from the first data storageformat.
 19. The article of claim 15, further comprising generating, bythe processor, a log entry corresponding to the request, wherein the logentry comprises at least one of a user identifier or an applicationidentifier.
 20. The article of claim 15, further comprising writing, bythe processor, data to the first variable in the first data storageformat in response to the request.